---
title: Governance lens
description: Learn about the Governance lens, which summarizes details of a deployment such as the owner, how the model was built, model age, and humility monitoring status.

---

#  Governance lens {: #governance-lens }

The Governance lens summarizes the social and operational aspects of a deployment, such as the deployment owner, how the model was built, the model's age, and the [humility monitoring](humble) status. View the governance lens from the [deployment inventory](deploy-inventory).

![](images/gov-lens-1.png)

The following table describes the information available from the Governance lens:

| Category     | Description     |
|--------------|-----------------|
| Deployment Name | The name assigned to a deployment at creation, the type of prediction server used, and the project name (DataRobot models only). |
| Build Environment | The environment in which the model was built. |
| Owners |  The [owner(s)](roles-permissions#deployment-roles) of each deployment. To view the full list of owners, click on the names listed. A pop-up modal displays the owners with their associated email addresses. |
| Model Age | The length of time the current model has been deployed. This value resets every time [the model is replaced](deploy-replace). |
| Humility Monitoring | The status of [prediction warnings](humility-settings#prediction-warnings) and humility [rules](humility-settings#create-humility-rules) for each deployment. |
| Fairness Monitoring | The status of [fairness rules](fairness-settings) based on the number of protected features below the predefined fairness threshold for each deployment.
|  Actions | Menu of additional [model management activities](actions-menu), including adding data, replacing a model, setting data drift, and sharing and deleting deployments. |

##  Build environments {: #build-environments }

The build environment indicates the environment in which the model was built.

![](images/gov-lens-2.png)

The following table details the types of build environments displayed in the inventory for each type of model:

|  Deployed model   | Available build environments |
|-------------------|------------------------------|
| DataRobot model  |  DataRobot  |
| Custom model     |  Python, R, Java, or Other (if not specified). Custom models derive their build environment from the model's programming language. |
| External model   |  DataRobot, Python, Java, R, or Other (if not specified). Specify an external model's build environment from the **Model Registry** when [creating a model package](reg-create#register-external-model-packages). |

## Humility Monitoring indicators {: #humility-monitoring-indicators }

The **Humility Monitoring** column provides an at-a-glance indication of how [humility is configured](humility-settings) for each deployment. To view more detailed information for an individual model, or enable humility monitoring, click on a deployment in the inventory list and navigate to the [**Humility**](humble) tab.

The column indicates the status of two Humility Monitoring features: [prediction warnings](humility-settings#prediction-warnings) and [humility rules](humility-settings).

In the deployment inventory, interpret the color indicators for each humility feature as follows:

|  Color | Status |
|--------|--------|
| ![](images/icon-humility-enabled.png) Blue          | Enabled for the deployment.  |
| ![](images/icon-humility-disabled.png) Light gray   | Disabled for the deployment. |
| ![](images/icon-humility-unavailable.png) Dark gray | Unavailable for the deployment. Humility Monitoring is only available for non-time-aware regression models and custom regression models that provide holdout data.|

## Fairness Monitoring indicators {: bias-and-fairness-monitoring indicators}

The **Fairness** column provides an at-a-glance indication of how each deployment is performing based on predefined [fairness](mlops-fairness) criteria. To view more detailed information for an individual model or enable fairness monitoring, click on a deployment in the inventory list and navigate to the **Settings** tab.

In the deployment inventory, interpret the color indicators as follows:

| Color                                     | Status |
|-------------------------------------------|--------|
| ![](images/icon-bias-gray.png) Light gray | Fairness monitoring is not configured for this deployment. |
| ![](images/icon-bias-green.png) Green     | All protected features are passing the fairness tests.     |
| ![](images/icon-bias-yellow.png) Yellow   | One protected feature is failing the fairness tests. Default is 1. |
| ![](images/icon-bias-red.png) Red         | More than one protected feature is failing the fairness tests. Default is 2. |

You can create rules for fairness monitoring in the [**Definition** section of the **Fairness > Settings**](fairness-settings#define-fairness-monitoring-notifications) tab. If no rules are specified, fairness monitoring uses the default values for "At Risk" and "Failing."